LLMOps: The Future of MLOps for Generative AI!

The progress in Large Language Models (LLMs) is fantastic, especially with the introduction of GPT-4 and DALL-E. These models have started a new era in AI and LLMs. GPT-4 is a massive model with 100 trillion parameters and was trained on 45 TB of text data. It’s more than 100 times bigger than the previous model and is 90% accurate. This progress has opened up new possibilities for the future of AI and language processing.

ChatGPT, an AI language model, shows that we’re close to breaking through the technology barrier with AI. Even though progress has been slow and steady over the years, the big challenge is still to successfully use AI on a large scale; as with earlier efforts to use AI, the hardest part is putting it into practice.

What are LLMOps?

LLMOps is a part of MLOps that focuses on Large Language Models (LLMs). It’s about the systems and operations needed to fine-tune basic models and use these improved models in a product. Even though LLMOps might not be a new idea for people familiar with MLOps, it is a more specialized part of this field. By looking at LLMOps more closely, we can better understand the specific needs for fine-tuning and using these models.

Big AI models like GPT-3 have 175 billion parameters and need much data and computing power to train. For…